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A 3D finite element model of the female pelvic floor for the reconstruction of urinary incontinence
(2014)
A concept for a sensitive micro total analysis system for high throughput fluorescence imaging
(2006)
This paper discusses possible methods for on-chip fluorescent imaging for integrated bio-sensors. The integration of optical and electro-optical accessories, according to suggested methods, can improve the performance of fluorescence imaging. It can boost the signal to background ratio by a few orders of magnitudes in comparison to conventional discrete setups. The methods that are present in this paper are oriented towards building reproducible arrays for high-throughput micro total analysis systems (µTAS). The first method relates to side illumination of the fluorescent material placed into microcompartments of the lab-on-chip. Its significance is in high utilization of excitation energy for low concentration of fluorescent material. The utilization of a transparent µLED chip, for the second method, allows the placement of the excitation light sources on the same optical axis with emission detector, such that the excitation and emission rays are directed controversly. The third method presents a spatial filtering of the excitation background.
A melting probe equipped with autofluorescence-based detection system combined with a light scattering unit, and, optionally, with a microarray chip would be ideally suited to probe icy environments like Europa’s ice layer as well as the polar ice layers of Earth and Mars for recent and extinct live.
A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
An increasing number of applications target their executions on specific hardware like general purpose Graphics Processing Units. Some Cloud Computing providers offer this specific hardware so that organizations can rent such resources. However, outsourcing the whole application to the Cloud causes avoidable costs if only some parts of the application benefit from the specific expensive hardware. A partial execution of applications in the Cloud is a tradeoff between costs and efficiency. This paper addresses the demand for a consistent framework that allows for a mixture of on- and off-premise calculations by migrating only specific parts to a Cloud. It uses the concept of workflows to present how individual workflow tasks can be migrated to the Cloud whereas the remaining tasks are executed on-premise.
The ANM’09 multi-disciplinary scientific program includes topics in the fields of "Nanotechnology and Microelectronics" ranging from "Bio/Micro/Nano Materials and Interfacing" aspects, "Chemical and Bio-Sensors", "Magnetic and Superconducting Devices", "MEMS and Microfluidics" over "Theoretical Aspects, Methods and Modelling" up to the important bridging "Academics meet Industry".
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.
An application of a scanning light-addressable potentiometric sensor for label-free DNA detection
(2013)
Mathematical morphology is a part of image processing that has proven to be fruitful for numerous applications. Two main operations in mathematical morphology are dilation and erosion. These are based on the construction of a supremum or infimum with respect to an order over the tonal range in a certain section of the image. The tonal ordering can easily be realised in grey-scale morphology, and some morphological methods have been proposed for colour morphology. However, all of these have certain limitations.
In this paper we present a novel approach to colour morphology extending upon previous work in the field based on the Loewner order. We propose to consider an approximation of the supremum by means of a log-sum exponentiation introduced by Maslov. We apply this to the embedding of an RGB image in a field of symmetric 2x2 matrices. In this way we obtain nearly isotropic matrices representing colours and the structural advantage of transitivity. In numerical experiments we highlight some remarkable properties of the proposed approach.